McKinsey, BCG et al engagements are very different from the stories typically depicted on blogs etc. Too often the writer seems intent on explain how long the hours are and the need to do analyses. That is part of the picture but far from the entire story. Many of these stories are also written bottom-up with an associate or analyst seeing things from their relatively narrow view without a proper feel for the higher level discussions.

This podcasts looks at things top-down from a partners perspective and we have culled together key lessons from the over +100 engagements each of the Firmsconsulting partners have done. We also focused on the “why” versus “what” happens on a typical study.

We have included elements from our days as associates but mainly analyzed things top-down to introduce a stronger element of the client issues.

Most people also have a romanticized view of management consulting work. Usually wrong. I therefore wanted to talk about my typically day/week as an associate (MBA level) consultant, and particularly how that changed as I moved up the ranks to the partnership. It will help you understand why mental math is so useful, as well as the extreme stresses of the job.

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Fantastic point at 8:00 about data. In the real world you’re very luck if you can find all the data you want, often you need to substitute proxy information (and clearly note your assumption). Additionally “cleaning” the data once you have it can be a significant task for any analyst (tip – record information on corrupt values, outliers, missing information, accuracy). Often clients I’ve worked with want to see their own data at this point and get your opinion of how “usable” it is, at which point it become an iterative process between the team and the client as you settle on an acceptable current state before even starting the analysis.

This is why, in my opinion, good consultants must use a decision tree up front to identify only the information you need to test your hypothesis. Boiling the ocean is a very real feeling if you ask for all the data and then have to clean and analyze all the data because you asked for it. This also opens your firm up to risk for information you gathered but didn’t use if there is ever an issue later on.